Research on the Semantic Analysis Method of Translation Corpus Based on Natural Language Processing

Abstract

Accurate recognition and analysis of semantics is the most important research field in the process of English translation with the help of natural language processing technology. This paper proposes an English semantic analysis method based on the neural network. First, the idea of model transfer is used to construct a topic segmentation model and the topic granularity segmentation of the translated text is carried out. Then, in order to obtain all the information in the English text, the recursive neural network is selected to recognize the word model. In order to recognize English texts with different sentence patterns, the long-Term and short-Term memory network is selected to extract the useful information of the text. Through the experimental data measurement and analysis results, compared with the traditional sentence analysis methods, the accuracy of the proposed method is as high as 95.8% and the model occupies less hardware resources.